Triple
T32550975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Uganda |
E831970
|
entity |
| Predicate | craneLegSymbolism |
P174917
|
FINISHED |
| Object | forward movement |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: forward movement | Statement: [flag of Uganda, craneLegSymbolism, forward movement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: craneLegSymbolism Context triple: [flag of Uganda, craneLegSymbolism, forward movement]
-
A.
treeSymbolism
Indicates the use of a tree as a symbolic representation of an idea, quality, or relationship between entities.
-
B.
fieldSymbolism
Indicates the symbolic meaning or thematic associations that a field (as a setting, area, or domain) conveys within a given context.
-
C.
explainsSymbolismOf
Indicates that one entity provides an interpretation or clarification of the symbolic meaning contained in another entity.
-
D.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
E.
vehicleSymbolism
Indicates the use of a vehicle as a symbolic representation of an idea, quality, or relationship between entities.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1:02 a.m.